Taking Your AI Projects from Pilot to Production

The rise of AI has made it possible for automated visual inspection systems to identify anomalies in manufactured products with high accuracy. If implemented successfully, these systems can greatly improve quality control and optimize costs. Although many manufacturers are trying to implement such systems into their workflow, very few have managed to reach full-scale production. The disconnect occurs because proof of concept solutions are put together in a controlled setting, largely by trial and error. However, when pushed into the real world with real-world constraints like variable environmental conditions, real-time requirements, and integrations with existing workflows, proof of concept often breaks down.